Autonomous vehicles are now reality on the battlefield and widespread acceptance and implementation are on the immediate horizon in other theaters of operation. The accuracy and precision of these self-driving systems depend upon the footprint or map of the area and objects in the vicinity of the vehicle whether moving or stationary. For optimal performance and safety, the field of view seen should be as wide as possible and should be able to be sampled at an extremely high frequency.
All autonomous vehicles have three cooperating systems. The vision system, which senses and interprets the distance between objects and the vehicle, the analytics system, which receives the visions system's constantly updating signals and performs speed and distance analysis via its software algorithms to generate a picture of the surrounding environment, and the control architecture system which receives inputs from the analytics system and converts them into mechanical actions of the vehicle such as steering, braking and acceleration.
The prior art vision systems vary in their theory of operation, however all send a signal and receive a reflected signal from which a composite image of size, shape and distance is compiled. It is this signal that is sent further to the analytics system for processing to generate vehicle control outputs to the control architecture system to safely guide the vehicle. Commonly utilized automobile vision systems embody electromagnetic radiation signals, such as can be found in LIDAR (Google), Radar (Tesla) and multi wavelength composite imaging (various small startup companies). All of these utilize some type of microprocessors running image processing software as part of the analytic system. However, none of these are particularly well suited to operating the self-driving vehicle with any degree of safety for two reasons: First, the frequency of their scans is too low, and second, their field of regard (also called instantaneous field of view, IFOV) is limited. This is also the case for unmanned aerial vehicles (UAVs) and semi- or fully autonomous driver assistants (ADA) presently in use.
While it may be theoretically possible to modify the current prior art systems to have a higher scan frequency and a larger field of regard, this would require a substantial input of energy as these systems utilize mechanical beam steering elements that operate either through movable deflection, MEMS devices or small rotating mirrors (galvanometer and rotating polygon systems). Any improved systems would have to be physically larger (and heavier), and would require much faster movement of the equipment to accomplish the desired, faster scan rate; this is a serious detriment to all vehicles, especially those that are fully electric.
Henceforth, an improved vision system of self-driving vehicles, having a low power consumption, a large field of regard (as close to 180 degrees in flat applications and 360 degrees in cylindrical applications), and extremely fast scan speeds (in excess of 75 KHz). would fulfill a long felt need in the autonomous vehicle industry. Although the transportation industry is only recently focused on autonomous modes of operation, the military has long been studying these and related problems. This new invention utilizes and combines known and new technologies in a unique and novel configuration to overcome the aforementioned limitations of the extant technology.